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Steve Aos Washington State Institute for Public Policy Phone: (360) 586-2740

K–12 Finance & Student Outcomes: Research Update Joint Task Force on Basic Education Finance November 20, 2007. Steve Aos Washington State Institute for Public Policy Phone: (360) 586-2740 E-mail: saos@wsipp.wa.gov Institute Publications: www.wsipp.wa.gov. 1 of 18.

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Steve Aos Washington State Institute for Public Policy Phone: (360) 586-2740

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  1. K–12 Finance & Student Outcomes: Research Update Joint Task Force on Basic Education Finance November 20, 2007 Steve Aos Washington State Institute for Public Policy Phone: (360) 586-2740 E-mail: saos@wsipp.wa.gov Institute Publications: www.wsipp.wa.gov 1 of 18

  2. Review of E2SSB 5627 Assignments… To the Task Force To the Institute 2 of 18

  3. Specific E2SSB 5627 Directive for WSIPP December 2007 Report to the Task Force • “At least two but no more than four options for allocating school employee compensation.” • “One of the options must be a redirection and prioritization within existing resources based on research-proven education programs.” (The zero-sum option) • “The report must also include a projection of the expected effect of the investment made under the new funding structure.” • And the report “shall also include a finalized timeline and plan for addressing the remaining components of a new funding system.” Today, I Will Talk About How Are We Approaching These Tasks 3 of 18

  4. “Costing Out” Methods Focused on Student Outcomes Four Approaches Limitations1 Used in WA Find “beat-the-odds” schools and emulate their resource and budget decisions. Successful School: Minor roles in Odden-Picus & Conley (WEA). Hard to identify beat- the-odds schools and/or emulate them. Professional Judgment: Gather a panel of educators who recommend a budget based on their experience & knowledge. Incentive to over-estimate needs. Schools may not follow model. Odden-Picus. Major role in Conley (WEA). Develop econometric models of actual school expenses and outcomes, then estimate costs. Regression Cost Studies: “Black box” problem; conflicting results from different assumptions. A minor role in Conley (WEA). Evidence-Based: Build prototype school budgets based on results from various evaluation studies. Research is limited on many topics; optimistic studies may be picked. Major role in Odden-Picus. Conley (WEA). 4 of 18 1. Source: Susanna Loeb (2007), “Difficulties in estimating the cost of achieving education standards.” University of Washington, School Finance Redesign Project, Daniel J Evans School of Public Affairs.

  5. Institute Research Approach • Our focus is on student outcomes (e.g. test scores, graduation rates) and how they are connected to funding levels and allocations. • Our method is a version of the evidence-based approach: • Include all higher-quality studies on a topic, not just one or two selected studies. • Take an average result to obtain a “betting persons” best estimate. • When research evidence is insufficient, say so. • As required, we are developing a model to project statewide student outcomes for different options. • Other research duties as directed by Task Force. E2SSB 5627: The funding structure developed by the Task Force “should be linked to accountability for student outcomes and performance.” 5 of 18

  6. Required December Institute Report to Task Force: Preliminary Analysis of Compensation-Related Options that Affect Student Outcomes • Base Case: more money into current system • Zero-Based Redirection: modify salary allocation schedule to reflect research-based findings on graduate degrees and experience. • Review of other options considered by Washington Learns K–12 advisory committee and in E2SSB 5627. 6 of 18

  7. 1 1 5 5 With Conley’s 45% 10 10 With Conley’s 45% 15 15 With O-P’s 26% 20 20 With O-P’s 26% 25 State Ranking: 1 = Highest PPE 25 30 30 35 35 40 40 Ranking Adjusted with NCES Comparable Wage Indices (1988 to 2005) 45 45 50 50 1970 1975 1980 1985 1990 1995 2000 2005 1970 1975 1980 1985 1990 1995 2000 2005 Per-Pupil K–12 Expenditures (PPE): View #1 Washington’s PPE Ranking Among the States: 1970 to 2005 Adjusted PPE (Comparable Wage Index) Unadjusted PPE Source: US Department of Education, National Center for Education Statistics. Data are for academic years 1969-70 to 2004-05. The Comparable Wage Index used here is a composite of the Comparable Wage Index by Lori Taylor (2007) and the General Wage Index by Dan Goldhaber (1999). “O-P” is the Odden-Picus report for Washington Learns and its25.7% increase (memo from J. Priddy, OSPI); “Conley” is the 44.8% from his study, published in 2007, for WEA . 7 of 18

  8. $10,000 United States (IPD) United States (CPI) United States $9,000 $8,000 $7,000 $6,000 $5,000 Washington (IPD) Washington (CPI) $4,000 Washington $3,000 $2,000 $1,000 $0 1970 1975 1980 1985 1990 1995 2000 2005 1970 1975 1980 1985 1990 1995 2000 2005 Per-Pupil K–12 Expenditures (PPE): View # 2 Nominal and Inflation-Adjusted PPE: 1970 to 2005 Inflation-Adjusted PPE (in 2005 dollars) Nominal PPE (Not Inflation-Adjusted) Source: US Department of Education, National Center for Education Statistics. Data are for academic years 1969-70 to 2004-05. The Comparable Wage Index used here is a composite of the Comparable Wage Index by Lori Taylor (2007) and the General Wage Index by Dan Goldhaber (1999). “O-P” is the Odden-Picus 25.7% increase (memo from J. Priddy, OSPI); “Conley” is the 44.8% from his study for WEA. 8 of 18

  9. 280 +4 +3 275 Washington +2 Washington 270 +1 0 265 -1 2005 NAEP 8th grade reading score Change in 8th Grade NAEP score 2003 to 2005 260 -2 -3 255 -4 250 -5 245 -6 $-800 $-600 $-400 $-200 $0 $200 $400 $600 $800 $1,000 $1,200 $1,400 $0 $2,000 $4,000 $6,000 $8,000 $10,000 $12,000 $14,000 $16,000 Change in CWI-Adjusted PPE: 2003 to 2005 Unadjusted PPE 2004-2005 Does spending more money in the current systems raise student outcomes? Before Considering Controlled Studies, Here are “Raw” Data for National Test Scores and PPE Change in NAEP score Unadjusted 2005 Data Change in Data, 2003 to 2005 Source: US Department of Education, National Center for Education Statistics. Test score data are for NAEP 8th grade reading test scores. The Comparable Wage Index developed by Lori Taylor (2007) for NCES was used in the “change in CWI-adjusted PPE” model shown here. 9 of 18

  10. Does spending more money in the current systems raise student outcomes? Change in NAEP score The unadjusted data on the previous slide are not a “study” that we would use (no controls, too high a level of aggregation). The small relationships shown with those state-level data are almost certainly an over-estimate of the effect of PPE on test scores. • Our 3-Step Evidence-Based Approach: • Review all higher-quality controlled studies addressing this question. • Take an average (weighted) of the results of these studies as the best estimate. • Project what the best estimate would mean to Washington in terms of key statewide student outcomes. 10 of 18 Before we show our preliminary results for the PPE question, we need to discuss two technical terms.

  11. Now suppose we found some K-12 program that raised student achievement by One Standard Deviation The Mean A Slightly Better Than Average Player….Steve Aos, 0.3 SD above the mean 1 Standard Deviation From Mean WASL“cut score” Best Player at Local Tumwater Club, 1.2 SD above the mean 2 Standard Deviations From Mean 3 Standard Deviations From Mean Roger Federer, 3.0 SD above mean 330 340 350 360 370 380 390 400 410 420 430 440 450 460 470 480 490 500 510 520 10th Grade WASL Reading Score, 2007 Methodological Diversion What Are “Effect Sizes” & “Standard Deviation” Units? Let’s Talk About the Distribution of Tennis Players Let’s Talk About the Distribution of Student WASL Scores • Effect Sizes and Standard Deviation Units are the main metrics used by education (and other) researchers to summarize findings. • In education research: Effect Sizes = Standard Deviation Units. A “Normal” Distribution 11 of 18

  12. Papke (2006) Ritzen & Winkler (1977) Levacic et al. (2005) Ritzen & Winkler (1977) Guryan (2003) Ritzen & Winkler (1977) Ritzen & Winkler (1977) Ferguson & Ladd (1996) Guryan (2003) Guryan (2003) Levacic et al. (2005) Guryan (2003) Sander (1999) Guryan (2003) Long (2006) Sander (1999) Lopus (1990) Guryan (2003) Kinnucan et al. (2006) Todd and Wolpin (2006) Todd and Wolpin (2006) Fuchs & Wößmann (2007) Long (2006) Sander (1999) Long (2006) Gyimah-Brempong & Gyapong (1991) Long (2006) Wilson (2001) Taylor (1997) Sander (1999) Gyimah-Brempong & Gyapong (1991) Haegeland et al. (2007) Loeb & Page (2000) Register & Grimes (1991) Fuchs & Wößmann (2007) Grimes (1994) Eide & Showalter (1998) Long (2006) Ferguson (1991) Long (2006) Long (2006) Grissmer et al. (2000) Fuchs & Wößmann (2007) Long (2006) Long (2006) Levacic et al. (2005) -0.02 -0.01 0 +.01 +.02 +.03 “Effect Size” in Standard Deviation Units on Student Test Scores for a 10% Increase in PPE Does an Increase in PPE Affect Student Outcomes? Research ApproachWe located and analyzed 46 results from 23 high quality studies we could find on this topic. Preliminary FindingA 10 percent increase in average PPE can boost student test scores by about .007 standard deviation units per year, per grade. 12 of 18

  13. 100% 95% With a 50% PPE Increase A 10% Increase in PPE could add about 1.3 percentage points to the graduation rate. 90% 85% 80% 75% 70% 65% 60% 55% 50% 2008 2010 2012 2014 2016 2018 2020 2022 2024 Changes to Per Pupil Expenditure (PPE) and Projected Statewide Student Outcomes Research ApproachAs directed by E2SSB 5627, we are building a model to estimate expected statewide effects of different options. Here we show some preliminary calculations. Estimated change in the high school graduation rate Graduation Rate Current OSPI On-Time High School Graduation Rate in Washington: 74.3% 13 of 18

  14. Required December Institute Report to Task Force: Preliminary Compensation-Related Options Affecting Student Outcomes • Base Case: more money into current system • Zero-Based Redirection: modify salary allocation schedule to reflect research-based findings on graduate degrees and experience. • Review of other options considered by Washington Learns K–12 advisory committee and those listed in E2SSB 5627. 14 of 18

  15. Research Update Teacher Effectiveness & Student Outcomes At the September Task Force meeting we reported a tentative finding from our research review:Effective Teachers Raise Student Outcomes… We can now add the following qualifier: …By Quite a Bit. 15 of 18

  16. Murnane & Phillips (1981) Murnane & Phillips (1981) Murnane & Phillips (1981) Hanushek (1992) Nye et al. (2004) Goldhaber & Brewer (1997) Clotfelter et al. (2007oct) Murnane & Phillips (1981) Hanushek (1992) Rowan et al. (2002) Krieg (2006) Koedel & Betts (2007) Nye et al. (2004) Rowan et al. (2002) Krieg (2006) A study with Washington WASL results Krieg (2006) Koedel & Betts (2007) Aaronson et al. (2007) Leigh (n.d.) Krieg (2006) Leigh (n.d.) Rockoff (2004) Rockoff (2004) Rivkin et al. (2005) Rockoff (2004) Kane et al. (2007) Kane et al. (2007) Rivkin et al. (2005) Rockoff (2004) 0 +0.1 +0.2 +0.3 +0.4 +0.5 “Effect Size” in Standard Deviation Units on Student Test Scores Effective Teachers and Student Outcomes Research ApproachWe located and analyzed 29 results from 13 high quality studies we could find on this topic. Preliminary FindingA teacher 1 standard deviation above average in effectiveness can boost student test scores from.1 to .4 standard deviation units per year; best estimate: .18 SD. 16 of 18

  17. A 1 standard deviation increase in system-wide teacher effectivenesscould add about 13 percentage points to the graduation rate. 100% 95% 90% 85% 80% 75% 70% 65% 60% 55% 50% 2008 2010 2012 2014 2016 2018 2020 2022 2024 Effective Teachers and Projected Student Outcomes Estimated change in the high school graduation rate Graduation Rate Current OSPI On-Time High School Graduation Rate in Washington: 74.3% 17 of 18

  18. High School WASL Math WASL Reading Graduation Rates, 2005 "Met-Standard" Rates, 2007 "Met-Standard" Rates, 2007 87% 87% 80% 85% 78% 78% 65% 68% 68% 61% 66% 60% 63% 62% 60% 55% 56% 31% 30% 26% 23% Low In- come Non- AI Asian Black His- White Low In- come Non- AI Asian Black His- White Low In- come Non- AI Asian Black His- White low AN* PI* panic low AN* PI* panic low AN* PI* panic * PI, AI, and AN are OSPI ethnic groupings for Pacific Islanders, American Indians, and Alaskan Natives. Source: OSPI Student Outcomes: High School Graduation and WASL “Met-Standard” Rates by Income Level and Ethnicity 18 of 18

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